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Third Workshop on New Trends in Content-based Recommender Systems (CBRecSys 2016)

Toine Bogers, Marijn Koolen, Cataldo Musto, Pasquale Lops, Giovanni Semeraro
2016 Proceedings of the 10th ACM Conference on Recommender Systems - RecSys '16  
The CBRecSys workshop provides a dedicated venue for papers dedicated to all aspects of content-based recommendation.  ...  While content-based recommendation has been applied successfully in many different domains, it has not seen the same level of attention as collaborative filtering techniques have.  ...  -Increasing diversity in content-based recommendations -Providing novelty in content-based recommendations '16 September 15-19, 2016, Boston , MA, USA © 2016 Copyright held by the owner/author(s).  ... 
doi:10.1145/2959100.2959200 dblp:conf/recsys/BogersKMLS16 fatcat:lnftrhy2und3bigw3spn73mt3u

RecSys Challenge 2016

Fabian Abel, András Benczúr, Daniel Kohlsdorf, Martha Larson, Róbert Pálovics
2016 Proceedings of the 10th ACM Conference on Recommender Systems - RecSys '16  
The 2016 ACM Recommender Systems Challenge focused on the problem of job recommendations.  ...  within the last days of the challenge.  ...  '16 September 15-19, 2016, Boston , MA, USA c 2016 Copyright held by the owner/author(s).  ... 
doi:10.1145/2959100.2959207 dblp:conf/recsys/AbelBKLP16 fatcat:te76gpxtajcc7ktwjnfdychjam

HCI for Recommender Systems

André Calero Valdez, Martina Ziefle, Katrien Verbert
2016 Proceedings of the 10th ACM Conference on Recommender Systems - RecSys '16  
Recommender-Systeme werden seit den 90er Jahren untersucht. Ihr Nutzen besteht darin, einen Benutzer durch die Dichte des Informationsdschungels zu nützlichen Wissensübersichten zu führen.  ...  , Boston, MA, USA § c 2016 Urheberrecht im Besitz des Inhabers/Autors(s).  ...  September 15-19, 2016 DIE ZUKUNFT Bibliometrische Analyse Aus der Scopus-Datenbank haben wir alle Dokumente aus dem Bereich der Informatik gesucht, die den Suchbegriff "Empfehlungssystem" enthielten  ... 
doi:10.1145/2959100.2959158 dblp:conf/recsys/ValdezZV16 fatcat:otjyud6ssnhkvijuap4znsbyhm

Automatic Leukocyte Image Segmentation: A review

Luis E. Hasbon Reyes, Lola X. Bautista Rozo, Fernando A. Rojas Morales
2015 2015 20th Symposium on Signal Processing, Images and Computer Vision (STSIVA)  
-10, Boston, MA, USA, August 2013.  ...  , pp. 81-84, Boston, MA, USA, August 2014.  ...  A Heuristic Approach to the Scheduling of Different Workloads in Internet-based Grids of Computers, Diaz, J., Reyes, S., Munoz-Caro, C Nino, A, The Second International Conference on Advanced Engineering  ... 
doi:10.1109/stsiva.2015.7330393 fatcat:gpelamofffeonj5njur5adpwv4

Exploring the Value of Personality in Predicting Rating Behaviors

Raghav Pavan Karumur, Tien T. Nguyen, Joseph A. Konstan
2016 Proceedings of the 10th ACM Conference on Recommender Systems - RecSys '16  
Prior work relevant to incorporating personality into recommender systems falls into two categories: social science studies and algorithmic ones.  ...  After controlling for the family-wise error rate, we find that High Agreeableness users rate at least 0.5 stars higher on a 5-star scale compared to low Agreeableness users.  ...  RecSys '16, September 15-19, 2016, Boston, MA, USA © 2016 ACM.  ... 
doi:10.1145/2959100.2959140 dblp:conf/recsys/KarumurNK16 fatcat:ldu3fsgwazgalpeat24ldg26km

Recommender Systems from an Industrial and Ethical Perspective

Dimitris Paraschakis
2016 Proceedings of the 10th ACM Conference on Recommender Systems - RecSys '16  
The second part of our research is still ongoing and focuses on various ethical challenges that complicate the design of recommender systems.  ...  Over the recent years, a plethora of recommender systems (RS) have been proposed by academics. The degree of adoptability of these algorithms by industrial e-commerce platforms remains unclear.  ...  RecSys '16, September 15 -19, 2016 , Boston , MA, USA of accuracy (measured in RMSE). After 10 years, the Netflix Prize still teaches us lessons.  ... 
doi:10.1145/2959100.2959101 dblp:conf/recsys/Paraschakis16 fatcat:bwwizsr2yfbfnleptucgoapkwy

Observing Group Decision Making Processes

Amra Delic, Julia Neidhardt, Thuy Ngoc Nguyen, Francesco Ricci, Laurens Rook, Hannes Werthner, Markus Zanker
2016 Proceedings of the 10th ACM Conference on Recommender Systems - RecSys '16  
Most research on group recommender systems relies on the assumption that individuals have conflicting preferences; in order to generate group recommendations the system should identify a fair way of aggregating  ...  Supported by these initial results we therefore advocate for the development of new group recommendation techniques that consider group dynamics and support the full group decision making process.  ...  ADDITIONAL AUTHORS Additional authors: Markus Zanker (Free University of Bozen-Bolzano, Bolzano, Italy, email: , Boston , MA, USA c 2016 Copyright held by the owner/author(s).  ... 
doi:10.1145/2959100.2959168 dblp:conf/recsys/DelicNNRRWZ16 fatcat:mamitxr3zvdehhpv5wva25qeeu

Hybrid Recommendation Scheme Based on Deep Learning

Fangpeng Ming, Liang Tan, Xiaofan Cheng, Xiao-dong Feng
2021 Mathematical Problems in Engineering  
In particular, the rise of the e-commerce industry has promoted the development of recommendation algorithms.  ...  Facing the complex and massive data, it is difficult for people to get the demanded information quickly, and the recommendation algorithm with its characteristics becomes one of the important methods to  ...  Yu, “Convolutional matrix factorization for document context-aware recom- mendation,” in Proceedings of the 10th ACM Conference on Recommender Systems, pp. 233–240, Boston, MA, USA,  ... 
doi:10.1155/2021/6120068 fatcat:rnj5hg6qhjh3fiyak7j6fcng5e

Multi-UAV Conflict Resolution with Graph Convolutional Reinforcement Learning

Ralvi Isufaj, Marsel Omeri, Miquel Angel Piera
2022 Applied Sciences  
Safety is the primary concern when it comes to air traffic.  ...  We implement an algorithm based on graph neural networks where cooperative agents can communicate to jointly generate resolution maneuvers.  ...  Dynamic Separation Thresholds for a Small Airborne Sense and Avoid System. In Proceedings of the AIAA Infotech@Aerospace (I@A) Conference, Boston, MA, USA, 19–22 August 2013. 47.  ... 
doi:10.3390/app12020610 fatcat:zv74eywngfh53h2chyxk4y4vke

Adaptive, Personalized Diversity for Visual Discovery

Choon Hui Teo, Houssam Nassif, Daniel Hill, Sriram Srinivasan, Mitchell Goodman, Vijai Mohan, S.V.N. Vishwanathan
2016 Proceedings of the 10th ACM Conference on Recommender Systems - RecSys '16  
Our system presents the user with a diverse set of interesting items while adapting to user interactions.  ...  scoring items based on category, and (3) personalized category preferences learned from the user's behavior.  ...  The authors thank Charles Elkan, Matthias Seeger, and the anonymous reviewers for their helpful comments.  ... 
doi:10.1145/2959100.2959171 dblp:conf/recsys/TeoNHSGMV16 fatcat:qzqzp35yd5bknetxk4mvvxxdma


Flavian Vasile, Elena Smirnova, Alexis Conneau
2016 Proceedings of the 10th ACM Conference on Recommender Systems - RecSys '16  
We show that the new item representa- tions lead to better performance on recommendation tasks on an open music dataset.  ...  Our method leverages past user interactions with items and their attributes to compute low-dimensional embeddings of items.  ...  RecSys '16, September 15-19, 2016 changes in recommendation [5] and handling the cold-start problem [29] .  ... 
doi:10.1145/2959100.2959160 dblp:conf/recsys/VasileSC16 fatcat:uhtv4xu7sfcu3orn73terweel4

Deep Neural Networks for YouTube Recommendations

Paul Covington, Jay Adams, Emre Sargin
2016 Proceedings of the 10th ACM Conference on Recommender Systems - RecSys '16  
YouTube represents one of the largest scale and most sophisticated industrial recommendation systems in existence.  ...  In this paper, we describe the system at a high level and focus on the dramatic performance improvements brought by deep learning.  ...  Sujeet Bansal, Shripad Thite and Radek Vingralek implemented key components of the training and serving infrastructure.  ... 
doi:10.1145/2959100.2959190 dblp:conf/recsys/CovingtonAS16 fatcat:d4ku6kfrundsnbqqs6wdf2vpf4

Muddling Label Regularization: Deep Learning for Tabular Datasets [article]

Karim Lounici and Katia Meziani and Benjamin Riu
2021 arXiv   pre-print
Our method, Muddling labels for Regularization (), penalizes memorization through the generation of uninformative labels and the application of a differentiable close-form regularization scheme on the  ...  Deep Learning (DL) is considered the state-of-the-art in computer vision, speech recognition and natural language processing.  ...  Wide & Deep Learning for Recommender Systems. In Proceedings of the 1st Workshop on Deep Learning for Recommender Systems, pages 7-10, Boston MA USA, September 2016. ACM.  ... 
arXiv:2106.04462v2 fatcat:4aarhtltffcxdphyhk4o3joope

A Systematic Comparison of Two Refactoring-aware Merging Techniques [article]

Max Ellis, Sarah Nadi, Danny Dig
2021 arXiv   pre-print
We compare RefMerge to Git and the state-of-the-art graph-based refactoring-aware merging tool, IntelliMerge, on 2,001 merge scenarios with refactoring-related conflicts from 20 open-source projects.  ...  We additionally conduct a qualitative analysis of the differences between the three merging algorithms and provide insights of the strengths and weaknesses of each tool.  ...  confessions of github contributors,” in Proceedings of the 2016 24th acm sigsoft international symposium on foundations of software engineering, 2016, pp. 858–870. [47] T. Mens and T.  ... 
arXiv:2112.10370v1 fatcat:hndbtajezbflhkfna5trmxoelq

Fifty Shades of Ratings

Evgeny Frolov, Ivan Oseledets
2016 Proceedings of the 10th ACM Conference on Recommender Systems - RecSys '16  
system.  ...  Conventional collaborative filtering techniques treat a top-n recommendations problem as a task of generating a list of the most relevant items.  ...  RecSys '16, September 15-19, 2016 , Boston, MA, USA. items. Randomly picking items for this purpose might be ineffective and frustrating for the user.  ... 
doi:10.1145/2959100.2959170 dblp:conf/recsys/FrolovO16 fatcat:fepqjkbgszh75p2sao5iacutei
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